Drug Delivery
achieve higher flow rates (two orders of magni- tude greater than flow focusing), and because there are commercially available systems based on this method designed specifically for the develop- ment and production of nanomedicines. ‘Ready- made’ systems like this remove the burden of instrument and chip design from drug develop- ment labs, overcoming the ‘knowledge gap’ tradi- tionally associated with microfluidics and allow- ing researchers to concentrate their efforts on the development of effective APIs.
No longer a black art
The highly-predictable mixing offered by these systems ensures the rapid, controlled production of a variety of nanoparticles. Optimising the geometry of the microfluidic chips maximises the interface between the fluid phases, allowing pre- cisely controlled mixing in milliseconds in nano- litre reaction volumes. Component mixing occurs faster than nanoparticle self-assembly, preventing sub-optimal mixing and heterogeneous precipita- tion, and the low energy conditions required are ideal for biologics. This standardisation of pro- cessing allows the production of nanoparticles with carefully defined characteristics, including chemical compositions, concentrations and drug/excipient ratios. Crucially, this approach also provides a clear route to scaling up produc- tion, as multiple identical chips can be run in par- allel. This allows throughput to be increased to meet the requirements of each phase of the drug development workflow, without changing the reaction conditions.
The flexibility and reproducibility of these auto- mated microfluidics platforms has revolutionised the way researchers are approaching nanoparticle development. By minimising batch-to-batch and
operator-to-operator variability, these systems allow accurate assessment of how changes in pro- cessing variables – drug and excipient concentra- tions, flow rates and mixing ratios – affect the structure and composition of the resulting nanoparticles, including average particle diameter, polydispersity (inhomogeneity) and drug encapsu- lation efficiency. This reproducibility means it is now possible to use a Design of Experiment (DoE) approach to rapidly assess and define the best parameters for robust manufacturing of any given nanoparticle, then screen lead formulations for the desired biological activity. And, because the final product is available in minutes, instead of several hours using conventional techniques, this helps to accelerate development timelines.
One of the biggest advantages of this approach is that the structure and behaviour of the resulting nanoparticles can be predicted according to the processing parameters and particle composition. Data generated by both the University of Strathclyde and Precision NanoSystems – for lipo- somes and polymeric particles respectively – illus- trates that processing parameters or particle com- positions can be fine-tuned to achieve the desired particles, enabling a more structured approach to nanomedicine research. By mapping out an approximate design space around the key process parameters for any given particle type and formu- lation, research groups can now quickly and easily screen and optimise their particles, allowing them to concentrate on in vivo drug function instead of particle manufacture.
Putting it to use
Due to the relative cost of nanomedicine formula- tions in comparison to simple dosage forms, such as pressed tablets, the areas most likely to benefit
Multiple microfluidic devices can perform the same operation in parallel to increase throughput
Drug Discovery World Fall 2017
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